基于群智仿生算法的大数据高效迁移策略研究

Research on big data efficient migration strategy based on swarm intelligence bionic algorithm

为了提高大数据迁移的执行效率并降低存储需求,提出采用群体仿生智能算法中的人工鱼群算法完成大数据迁移过程。首先,根据鱼群活动状态对大数据迁移进行策略分析,并对数据记录及存储空间按照鱼群算法进行建模。然后,采用存储范围和迁移步长动态变化的策略完成大数据自动迁移。经过实验证明,相比LRU迁移算法,基于人工鱼群算法的数据迁移策略在存储空间及执行时间消耗方面优势明显,具有一定的推广价值。

In order to improve the execution efficiency of big data migration and reduce the storage demands,the artificial fish swarm algorithm in the swarm intelligence algorithm is proposed to complete the big data migration process. The strategy analysis of big data migration is carried out according to the fish population activity status,and the data record and storage space are modeled according to the fish swarm algorithm. The automatic migration of big data is completed by a strategy of dynamically changing the storage range and the migration step size. Experiment results show that,in comparison with the LRU migration algorithm,the data migration strategy based on artificial fish swarm algorithm has more obvious advantages in storage space and execution time consumption,and has a certain promotion value.